Stroke genetics informs drug discovery and risk prediction across ancestries

Previous genome-wide association studies (GWASs) of stroke — the second leading cause of death worldwide — were conducted predominantly in populations of European ancestry1,2. Here, in cross-ancestry GWAS meta-analyses of 110,182 patients who have had a stroke (five ancestries, 33% non-European) and 1,503,898 control individuals, we identify association signals for stroke and its subtypes at 89 (61 new) independent loci: 60 in primary inverse-variance-weighted analyses and 29 in secondary meta-regression and multitrait analyses. On the basis of internal cross-ancestry validation and an independent follow-up in 89,084 additional cases of stroke (30% non-European) and 1,013,843 control individuals, 87% of the primary stroke risk loci and 60% of the secondary stroke risk loci were replicated (P < 0.05). Effect sizes were highly correlated across ancestries. Cross-ancestry fine-mapping, in silico mutagenesis analysis3, and transcriptome-wide and proteome-wide association analyses revealed putative causal genes (such as SH3PXD2A and FURIN) and variants (such as at GRK5 and NOS3). Using a three-pronged approach4, we provide genetic evidence for putative drug effects, highlighting F11, KLKB1, PROC, GP1BA, LAMC2 and VCAM1 as possible targets, with drugs already under investigation for stroke for F11 and PROC. A polygenic score integrating cross-ancestry and ancestry-specific stroke GWASs with vascular-risk factor GWASs (integrative polygenic scores) strongly predicted ischaemic stroke in populations of European, East Asian and African ancestry5. Stroke genetic risk scores were predictive of ischaemic stroke independent of clinical risk factors in 52,600 clinical-trial participants with cardiometabolic disease. Our results provide insights to inform biology, reveal potential drug targets and derive genetic risk prediction tools across ancestries

Combined Pre-Treatment Technologies for Cleaning Biogas before Its Upgrading to Biomethane: An Italian Full-Scale Anaerobic Digester Case Study

Biogas produced by anaerobic digestion contains different types of contaminants, and it is preferable to eliminate those contaminants before biogas’ energetic valorization or upgrading to biomethane as they are harmful to human health and detrimental to combustion engines. This study presents the biogas cleanup system optimized by an Italian full-scale anaerobic digester treating food waste (FW) and represented by micro-oxygenation, chemical scrubber, cooling, and activated carbon sections. The cleaned biogas is upgraded to biomethane using a membrane-based upgrading unit and injected into the natural gas network for transport sector use. H2S and volatile organic compound (VOC) concentration in raw biogas was reduced from an annual average value of 1207 ppmv and 895 mg/Nm3, respectively, to below 0.1 mg/Nm3 in the final biomethane. In the summer, the H2S average content in raw biogas was 833 ppmv due to a greater presence of low-sulfur-containing vegetables in FW, while in the winter it was an average of 1581 ppmv due to a larger portion of protein-containing FW. On the other hand, raw biogas VOC content in the winter was an average of 1149 mg/Nm3, with respect to 661 mg/Nm3 in the summer, due to the greater consumption of citrus fruits containing high amount of terpene compounds. The concentration of other trace contaminants, such as HCl, NH3, and siloxanes, was lowered from 17, 36, and 0.6 mg/Nm3 in raw biogas, respectively, to below 0.1 mg/Nm3 in the final biomethane. All the considerations and evaluations underlying the technological and plant engineering choices together with the individuation of the best operating conditions are discussed

Pyrolysis and Gasification of a Real Refuse-Derived Fuel (RDF): The Potential Use of the Products under a Circular Economy Vision

Refuse-Derived Fuels (RDFs) are segregated forms of wastes obtained by a combined mechanical&ndash;biological processing of municipal solid wastes (MSWs). The narrower characteristics, e.g., high calorific value (18&ndash;24 MJ/kg), low moisture content (3&ndash;6%) and high volatile (77&ndash;84%) and carbon (47&ndash;56%) contents, make RDFs more suitable than MSWs for thermochemical valorization purposes. As a matter of fact, EU regulations encourage the use of RDF as a source of energy in the frameworks of sustainability and the circular economy. Pyrolysis and gasification are promising thermochemical processes for RDF treatment, since, compared to incineration, they ensure an increase in energy recovery efficiency, a reduction of pollutant emissions and the production of value-added products as chemical platforms or fuels. Despite the growing interest towards RDFs as feedstock, the literature on the thermochemical treatment of RDFs under pyrolysis and gasification conditions still appears to be limited. In this work, results on pyrolysis and gasification tests on a real RDF are reported and coupled with a detailed characterization of the gaseous, condensable and solid products. Pyrolysis tests have been performed in a tubular reactor up to three different final temperatures (550, 650 and 750 &deg;C) while an air gasification test at 850 &deg;C has been performed in a fluidized bed reactor using sand as the bed material. The results of the two thermochemical processes are analyzed in terms of yield, characteristics and quality of the products to highlight how the two thermochemical conversion processes can be used to accomplish waste-to-materials and waste-to-energy targets. The RDF gasification process leads to the production of a syngas with a H2/CO ratio of 0.51 and a tar concentration of 3.15 g/m3

Multi-phenotype analyses of hemostatic traits with cardiovascular events reveal novel genetic associations

Multi-phenotype analysis of genetically correlated phenotypes can increase the statistical power to detect loci associated with multiple traits, leading to the discovery of novel loci. This is the first study to date to comprehensively analyze the shared genetic effects within different hemostatic traits, and between these and their associated disease outcomes. To discover novel genetic associations by combining summary data of correlated hemostatic traits and disease events. Methods: Summary statistics from genome wide-association studies (GWAS) from seven hemostatic traits (factor VII [FVII], factor VIII [FVIII], von Willebrand factor [VWF] factor XI [FXI], fibrinogen, tissue plasminogen activator [tPA], plasminogen activator inhibitor 1 [PAI-1]) and three major cardiovascular (CV) events (venous thromboembolism [VTE], coronary artery disease [CAD], ischemic stroke [IS]), were combined in 27 multi-trait combinations using metaUSAT. Genetic correlations between phenotypes were calculated using Linkage Disequilibrium Score Regression (LDSC). Newly associated loci were investigated for colocalization. We considered a significance threshold of 1.85 × 10 obtained after applying Bonferroni correction for the number of multi-trait combinations performed (n = 27). Across the 27 multi-trait analyses, we found 4 novel pleiotropic loci (XXYLT1, KNG1, SUGP1/MAU2, TBL2/MLXIPL) that were not significant in the original individual datasets, were not described in previous GWAS for the individual traits, and that presented a common associated variant between the studied phenotypes. The discovery of four novel loci contributes to the understanding of the relationship between hemostasis and CV events and elucidate common genetic factors between these traits

Multi-phenotype analyses of hemostatic traits with cardiovascular events reveal novel genetic associations

Background: Multi-phenotype analysis of genetically correlated phenotypes can increase the statistical power to detect loci associated with multiple traits, leading to the discovery of novel loci. This is the first study to date to comprehensively analyze the shared genetic effects within different hemostatic traits, and between these and their associated disease outcomes. Objectives: To discover novel genetic associations by combining summary data of correlated hemostatic traits and disease events. Methods: Summary statistics from genome wide-association studies (GWAS) from seven hemostatic traits (factor VII [FVII], factor VIII [FVIII], von Willebrand factor [VWF] factor XI [FXI], fibrinogen, tissue plasminogen activator [tPA], plasminogen activator inhibitor 1 [PAI-1]) and three major cardiovascular (CV) events (venous thromboembolism [VTE], coronary artery disease [CAD], ischemic stroke [IS]), were combined in 27 multi-trait combinations using metaUSAT. Genetic correlations between phenotypes were calculated using Linkage Disequilibrium Score Regression (LDSC). Newly associated loci were investigated for colocalization. We considered a significance threshold of 1.85 × 10−9 obtained after applying Bonferroni correction for the number of multi-trait combinations performed (n = 27). Results: Across the 27 multi-trait analyses, we found 4 novel pleiotropic loci (XXYLT1, KNG1, SUGP1/MAU2, TBL2/MLXIPL) that were not significant in the original individual datasets, were not described in previous GWAS for the individual traits, and that presented a common associated variant between the studied phenotypes. Conclusions: The discovery of four novel loci contributes to the understanding of the relationship between hemostasis and CV events and elucidate common genetic factors between these traits